Explore Consumers’ Willingness to Purchase Biotechnology Produced Fruit: An International Study
Bibliographic record
Abstract
While food biotechnology has been widely applied and benefited the food and agriculture sector, community acceptance of biotechnology is still low. The factors that drive consumer rejection of food biotechnology have been well studied, but knowledge on the factors that drive willingness to purchase, particularly on an international level, is limited. This study aims to identify driving factors for respondents’ willingness to purchase fresh fruit produced with biotechnology, using an international survey conducted in the US, Canada, UK, France, and South Korea. While the overall willingness to purchase biotechnology produced fruit is low across countries, French consumers have the highest rate of willingness to purchase biotechnology produced fresh fruit among studied countries, followed by South Korea. The factors influencing respondents’ willingness to purchase include demographics, lifestyle, and shopping behavior. While respondents behave differently across countries, factors like environmental awareness, self-reported healthiness, and habits of eating away from home, have been found to enhance the willingness to purchase biotechnology produced fruit across countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".